Machine Learning of Wind Plant Turbulence Anisotropy Fields

In studies of wind plant designs, wake dynamics are of great interests as wakes affect downstream turbine loading that impacts wind plant efficiency. Recent developments of Tensor Basis Decision Tree (TBDT) based machine learning (ML) models in reconstructing the turbulence anisotropy fields of simple flow cases prompt the motivation in applying...

Prediction of flow-fields by combining high-fidelity CFD data and Machine Learning algorithms

High-fidelity optimisation studies are a useful asset in the design of critical components for large gas turbines. These studies require the computation of numerous computationally expensive CFD simulations and result in predominantly optimisation graphs of design objectives (e.g. Pareto-front figure). The quantity of generated data is...